Title |
A Conceptual Framework to Support Decision-Making in Remanufacturing Engineering Processes |
ID_Doc |
8937 |
Authors |
Alghamdi, A; Prickett, P; Setchi, R |
Title |
A Conceptual Framework to Support Decision-Making in Remanufacturing Engineering Processes |
Year |
2017 |
Published |
|
DOI |
10.1007/978-3-319-57078-5_22 |
Abstract |
Remanufacturing is a promising industrial activity where products and materials are upgraded and considered for at least another life cycle. In addition to being an environmentally conscious action, remanufacturing has the potential to support circular economy within which significant profit opportunities exist. However, high levels of uncertainty can be experienced during, before and after remanufacturing. This makes its planning stochastic and hard to control. As each component or product is different, with for example high levels of geometrical variation; they may require a unique strategy and process planning. To aid this process, a conceptual decision making framework to support process planning of remanufacturing engineering processes (REP) is proposed. Quality Function Deployment (QFD) method is employed to support the proposed framework (hereafter referred to as REP-QFD). The application of the QFD based methods rely heavily on inputs from experts, in the form of their experience and knowledge. The paper considers how the proposed framework can be engineered with the aim to substantially reduce this reliance on experts and their expertise. The term "Engineering" here reflects the study's focus on technical decisions at the reconditioning stage. To further support the framework a taxonomy of metal manufacturing/remanufacturing processes is also developed. |
Author Keywords |
Remanufacturing; Manufacturing; Decision making; House of quality; QFD; Repair processes; Uncertainty; Additive manufacturing (AM) |
Index Keywords |
Index Keywords |
Document Type |
Other |
Open Access |
Open Access |
Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
EID |
WOS:000419074600022 |
WoS Category |
Engineering, Manufacturing |
Research Area |
Engineering |
PDF |
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